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Multi-temporal InSAR evidence of non-tidal ocean loading effects from Chaoshan coastal plain, China
- Source :
- International Journal of Applied Earth Observations and Geoinformation, Vol 132, Iss , Pp 104031- (2024)
- Publication Year :
- 2024
- Publisher :
- Elsevier, 2024.
-
Abstract
- Ocean loading deformation is one of the key processes in geodesy, geophysics, and Isostasy, and is also important for assessment of future coastal environmental changes. Traditionally, the ocean tide loading has been considered the only contributor to the ocean loading deformation by most previous InSAR (Interferometric Synthetic Aperture Radar) studies. In this study, we quantify the non-tidal ocean loading deformation using the multi-temporal InSAR-derived deformation data from the Chaoshan coast in southern China and explore its driving mechanisms. Our results show that InSAR deformation anomalies in the Chaoshan coastal area exhibit a distinct deformation gradient from the coast to inland. A strong scale- and direction-dependent pattern in InSAR data, with significant seasonality, is unveiled by the second-order spatial structure function. To explore the driving mechanism behind this deformation, we conduct a correlation analysis between spatial pattern of land deformation and sea level changes. The results indicate that ocean loading is the predominant driving factor behind the Chaoshan coastal deformation. Analysis using the MERRA2 model demonstrates that terrestrial water storage loading deformation is negligible in comparison. Furthermore, by applying the FES2014b tide model, we find that the contributions of the non-tidal and tide-induced ocean loading deformation to the total deformation anomaly are 50–70% and 30–50%, respectively. Lastly, we have uncovered that the non-tidal ocean loading is primarily attributed to the monsoon-induced seasonal sea level changes, with a time lag ranging from one to two months. Quantifying non-tidal ocean loading deformation provides valuable insights to large-scale high-precision coastal InSAR applications.
Details
- Language :
- English
- ISSN :
- 15698432
- Volume :
- 132
- Issue :
- 104031-
- Database :
- Directory of Open Access Journals
- Journal :
- International Journal of Applied Earth Observations and Geoinformation
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.5e311a7ed5a4426a91361b168542cf94
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.jag.2024.104031